Hi, Jimmy,
If X and Y are continuous, then the probability of their assuming
particular fixed values is of course 0.
If X and Y are discrete, then you can run the simulation with lots of
iterations (depending on the number of possible combinations of values
of X and Y), extract the simulation data, and sort on X then Y. Simple
counting will allow you to calculate the desired conditional probability.
Regards,
Jim

--- In cbug2@yahoogroups.com, "asujames" <asujames@...> wrote:
>
> Hello all,
>
> I'm trying to model conditional proabailities in CB. Quick
> desscribtion of my problem.
>
> I have three distributions as inputs (X, Y, Z) and I run my MC to get
> output F. There is a correlation between X and Z and Y and Z. I want
> to be able to specify X and Y and run my simulation, but at the same
> time I want the correleation between the distributiuons to remain.
> Because of this I can't just set X and Y to a value and run because
> CB defines the correlations to assumptions.
>
> What I have done. I tried to use the 2D simulation tool to perform
> thsi task, which seemed liek it shodul work because it will set X and
> Y and then run the MC for Z and forcast my output F. The porbelm is
> the corrleatiosn do not remain between X and Z or Y and Z. So I can
> get a conditional probability for F but it doesn't include a
> crrelation ebwteen my inputs.
>
> The goals is to determin the 99th confidence for F given a X and Y,
> and running MC all all of my other inputs in thsi case just Z and
> keeping the correlations between my inputs.
>
> Has anyone tried to answer a simular type of problem and can help or
> maybe you see a solution that I'm missing
>
> Thanks
>
> jimmy
>